Our model was trained on TRIPOD\(\bigoplus \) , an expanded version of the
TRIPOD dataset [1]}, [2]} which
contains 122 screenplays with silver-standard TP annotations
(scene-level)https://github.com/ppapalampidi/TRIPOD and the corresponding videos.https://datashare.ed.ac.uk/handle/10283/3819 For each movie, we further
collected as many trailers as possible from YouTube, including
official and (serious) fan-based ones, or modern trailers for older
movies. To evaluate the trailers produced by our algorithm, we also
collected a new held-out set of 41 movies. These movies were selected
from the Moviescope datasethttp://www.cs.virginia.edu/ pc9za/research/moviescope.html [3]}, which
contains official movie trailers. The held-out set does not contain
any additional information, such as screenplays or TP annotations. The
statistics of TRIPOD\(\bigoplus \)  is presented in
Table REF .
<TABLE>